Biology subjects

zhao, z.

Publications and source records attributed to zhao, z..

4 recordsLinked to original sources

bioRxiv2026

Genomic Foundation Models Reveal Chromatin-Domain-Scale Transposable Element Impacts on Rice Genome Architecture

Alignment-based detection of transposable element (TE) insertion polymorphisms suffers from reference bias and multi-mapping errors in repetitive genomic regions, creating a fundamental validation bottleneck for population-scale structural variant catalogs. Here, we demonstrate that the OneGenome-Rice (OGR) genomic foundation model (GFM)--a 1.25 billion parameter Mixtral architecture trained on 422 rice genomes without TE annotations--provides an entirely orthogonal, alignment-free approach that resolves TE-mediated structural divergence at chromatin-domain resolution. At the CTB4a cold-tolerance locus on chromosome 4, OGR embeddings revealed that the aus subpopulation (NONA_BOKRA) carries 2.2-fold higher structural divergence from indica than japonica, consistent with its 728 subpopulation-exclusive cold-protective TE insertions. Sliding-window analysis across 4.4 megabases identified a 25.6-fold divergence enhancement at TE clusters relative to the conserved CTB4a gene body. Critically, the minimal effective resolution was established at approximately 20 kilobases--corresponding to the median size of topologically associating domains (TADs) in the rice genome--while individual TE sites at 500 base pairs were undetectable (P = 0.94). Non-neural baselines confirmed the signal derives from learned representations of genomic context rather than simple nucleotide statistics. These findings establish GFMs as orthogonal validation tools for population-scale TE genotyping and provide computational evidence that TE functional effects are organized at the chromatin-domain level, with direct implications for prioritizing functional TE variants in crop breeding.

plant biology↗

bioRxiv2025

Resolving Heterogeneity in Major Depression: Overcoupling and Undercoupling Subtypes Exhibit Differential Treatment Response and Molecular Pathways

Major depressive disorder (MDD) exhibits significant heterogeneity whose neurobiological mechanisms remain elusive. Alterations in morphological-functional coupling (MFC) have been observed in MDD. This study aims to investigate MDD subtypes based on MFC alterations and their associations with clinical symptoms and molecular basis. We identified two clinically distinct MDD subtypes in multi-center neuroimaging data (Discovery: 828 MDD/776 healthy controls; Validation: 236 MDD/86 healthy controls) by using a semi-supervised machine learning approach based on MFC changes, which were validated and robustly repeated in the validation dataset. Differences among subtypes were then examined in relation to clinical assessments, gene expression patterns, neurotransmitter and cell density, and treatment response. Subtype I (overcoupling) showed elevated MFC in high-order association cortices, linking to synaptic transmission activity and severe symptoms. Subtype II (undercoupling) demonstrated reduced MFC in primary cortices, associated with cell cycle regulation and treatment resistance. Both subtypes shared molecular signatures (cell types: astrocytes and oligodendrocytes; neurotransmitter systems: serotonergic and GABAergic receptors). Crucially, longitudinal data (33 MDD undergoing Escitalopram monotherapy) revealed that undercoupling subtype exhibited better response, implying a potential mechanism of the drug via increasing the MFC. Our work deciphers MFC-driven MDD phenotypes with distinct molecular profiles and differential treatment outcomes, suggesting potential pathways for personalized diagnosis and treatment strategies in MDD, advancing precision psychiatry.

neuroscience↗

bioRxiv2025

Integrating molecular and physiological approaches to quantify genetic controls for wheat development and improve phenotyping

Disentangling genotype x environment (GxE) effects is critical to understand the performance of wheat across different environments. A framework for doing this was previously presented in a model that integrated knowledge of crop physiology and the Vrn gene feedback loop to explain and predict the time of anthesis. The aims of this study were: 1) provide an updated description of the Cereal Anthesis Molecular Phenology (CAMP) model; 2) to verify the models assumptions regarding the relationship between Vrn gene expression and the timing of phenological stages in a set of diverse genotypes and environments; 3) to use the CAMP model to establish a phenotyping strategy for use in genetic studies and model parameterisation. Six wheat genotypes with a range of cool temperature and photoperiod sensitivities were evaluated. Apical development, final leaf number (FLN) and temporal expression of Vrn1, Vrn2 and Vrn3 were compared with model predictions. There was a clear relationship between FLN responses to cool temperature and photoperiod, the timing of phenological events and the patterns of Vrn gene expression for all genotypes. There was general agreement between the temporal patterns of foliar gene expression observed with those assumed by CAMP, but some obvious discrepancies. These may be related to differences between gene expression in foliar (observed) and apical (assumed by the model) parts of the plant, or differences in the way observed and modelled gene expression are scaled. Overall, the model described all the observed development responses to environment and provides a basis for building quantitative predictions of field-based development from genotypic and environmental data. A protocol is presented for phenotyping wheat using FLN measured in specific combinations of temperature and photoperiod. It allows easy and unconfounded measure of key developmental phenotypes that clearly relate to the genetic make-up of the plants and underlying gene expression profiles.

plant biology↗

bioRxiv2019

Long noncoding RNA AVAN promotes antiviral innate immunity by interacting with TRIM25 and enhancing the transcription of FOXO3a

Accumulating evidence has shown that long noncoding RNAs (lncRNAs) are involved in several biological processes, including immune responses. However, the role of lncRNAs in antiviral innate immune responses remains largely unexplored. Here, we identify an uncharacterized human lncRNA from influenza A virus (IAV) patients, antivirus and activate neutrophil (AVAN), that is significantly up-regulated upon virus infection. Mechanistically, nuclear lncRNA-AVAN positively regulates the transcription of forkhead box O3A (FOXO3a) by associating with its promoter and inducing chromatin remodeling to promote neutrophil chemotaxis. Furthermore, we also found that cytoplasmic lncRNA-AVAN directly binds tripartite motif containing 25 (TRIM25) and enhances the association of TRIM25 and Retinoic acid inducible gene-1 proteins (RIG-I) and the ubiquitylation of RIG-I, thereby promoting TRIM25- and RIG-I-mediated antiviral innate immune signaling. More importantly, we enforced the expression of AVAN in transgenic mice and found that it significantly alleviated IAV virulence and virus production. Collectively, these findings highlight the potential clinical implications of lncRNA-AVAN as a key positive regulator of the antiviral innate immune response and a promising target for developing broad antiviral therapeutics.

immunology↗